Automated sleep apnea diagnosis through mandibular movement monitoring coupled with machine learning analysis

Pépin, J. L., Letesson, C., Le-Dong, N.N., Dedave, A., Denison, S., Cuthbert, V., Martinot, J., Gozal, D.

Obstructive sleep apnea (OSA) affects almost 1 billion people worldwide, resulting in high socioeconomic and health care burden. Excessive daytime sleepiness and fatigue, the chief problems reported by patients with OSA, may have negative consequences on neurocognitive function, mood, and productivity at work, leading to decreased quality of life and increased risk of occupational injuries and motor vehicle crashes. Obstructive sleep apnea is also a major risk factor for a variety of medical conditions, increasing the risk and severity of cardiometabolic diseases, including hypertension, arrhythmias, stroke, coronary heart disease, type 1 and type 2 diabetes, and metabolic dysfunction, ultimately resulting in increased overall mortality. Continuous positive airway pressure, the first-line therapy for OSA, is effective in alleviating symptoms, restoring neurocognitive function, and improving quality of life. Although OSA is one of the most prevalent chronic diseases associated with a wide range of disabilities, it remains an underdiagnosed health problem.